Summary. When it comes to leveraging data to improve their day-to-day operations, organizations need to look beyond building a team of skilled data professionals and arming it with the latest analytics tools and technologies. A well-equipped analytics team is a necessary condition of using data to drive business value, but it’s not a sufficient one. To more actively contribute to the achievement of critical business outcomes, analytics teams should start viewing their random forests and neural networks through a product development lens. By bringing a product development approach to the planning and execution of analytics, organizations can scale isolated successes into the kind of sustained, organization-wide, data-driven decision-making that serves as the foundation of genuine digital transformation.close
According to an International Data Corporation (IDC) report, at least half of global GDP will be digitized by 2021. Unfortunately, as the report explains, “While most organizations are attempting [digital transformation], only a small percentage are getting it right.”
In most cases, the tech isn’t the problem. Many organizations’ failure to adapt to a highly digitized business landscape stems from their inability to convince employees to embrace data-driven decision-making. A NewVantage Partners survey found that 48% of executives cite “people challenges” as the foremost barrier to being more data-driven as an organization, compared to just 19% who cite “technology.” As such, while a well-equipped analytics team is a necessary condition of using data to drive business value, organizations need to look beyond building a team of skilled data professionals with the latest analytics tools and technologies if they want to leverage data to improve their day-to-day operations.
To more actively contribute to the achievement of critical business outcomes, analytics teams should start viewing their random forests and neural networks through a product development lens. By bringing a product development approach to the planning and execution of analytics, organizations can scale isolated successes into the kind of sustained, organization-wide, data-driven decision-making that serves as the foundation of genuine digital transformation.

Using Analytics Solutions to Address Unmet Needs
Adoption is the key metric of product development, and as such, identifying — and addressing — end users’ unmet needs is a central imperative of nearly every product development methodology. Acting on this imperative requires analytics professionals to take a step outside their comfort zones and assume more collaborative roles than they are accustomed to.
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